ANOVA (ANalysis Of VAriance) is a statistical test to determine whether two or more population means are different. In other words, it is used to compare two or more groups to see if they are significantly different.
Note that there are several versions of the ANOVA (e.g., one-way ANOVA, two-way ANOVA, mixed ANOVA, repeated measures ANOVA, etc.). In this tutorial, we present the simplest form only—the one-way ANOVA—and we refer to it as ANOVA in the tutorial.
In this tutorial, we discuss about ANOVA from a practical point of view, and in particular we will cover the following points:
- the aim of the ANOVA, when it should be used and the null/alternative hypothesis
- the underlying assumptions of the ANOVA and how to check them
- how to perform the ANOVA in R
- how to interpret results of the ANOVA
- understand the notion of post-hoc test and interpret the results
- how to visualize results of ANOVA and post-hoc tests
You'll learn when to use an ANOVA, how to perform it in R, and how to interpret the results. Ask any questions related to the content for free!